Abstract
Electric vehicle (EV) sharing has experienced rapid development and has served as a flexible and environmental friendly means for urban transportation. However, charging an EV sharing fleet is still a challenge for business operators because of limited or costly access to charging facilities. In this chapter, we focus on how to charge a fleet to make EV sharing viable and profitable. Adopting the real data of car2go, we propose a queueing network model to characterize how customers endogenously pick EVs according to energy levels, as well as the implementation of a charging-up-to policy. In order to solve the proposed nonlinear optimization program, we develop mixed-integer second order cone programs as tractable lower- and upper-bound formulations. These models lead to practical insights related to charger resource availability and locations, EV charging policy, battery technological advancements, and urban spatial structure.
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He, L., Ma, G., Qi, W., Wang, X., Hou, S. (2022). Planning and Management of Charging Facilities for Electric Vehicle Sharing. In: Pardalos, P.M., Rassia, S.T., Tsokas, A. (eds) Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities. Springer Optimization and Its Applications, vol 186. Springer, Cham. https://doi.org/10.1007/978-3-030-84459-2_8
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DOI: https://doi.org/10.1007/978-3-030-84459-2_8
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